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Apply isort and ruff code style

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This commit is contained in:
Michael Osthege
2024-10-03 11:05:44 +02:00
committed by Andreas
parent 05a3c1a5bb
commit a4d178d250
23 changed files with 1787 additions and 866 deletions
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48
modules/class_load.py
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@@ -1,9 +1,10 @@
import numpy as np
from datetime import datetime
from pprint import pprint
import numpy as np
# Load the .npz file when the application starts
class LoadForecast:
def __init__(self, filepath=None, year_energy=None):
self.filepath = filepath
@@ -15,37 +16,41 @@ class LoadForecast:
def get_daily_stats(self, date_str):
"""
Returns the 24-hour profile with mean and standard deviation for a given date.
:param date_str: Date as a string in the format "YYYY-MM-DD"
:return: An array with shape (2, 24), contains means and standard deviations
"""
# Convert the date string into a datetime object
date = self._convert_to_datetime(date_str)
# Calculate the day of the year (1 to 365)
day_of_year = date.timetuple().tm_yday
# Extract the 24-hour profile for the given date
daily_stats = self.data_year_energy[day_of_year - 1] # -1 because indexing starts at 0
daily_stats = self.data_year_energy[
day_of_year - 1
] # -1 because indexing starts at 0
return daily_stats
def get_hourly_stats(self, date_str, hour):
"""
Returns the mean and standard deviation for a specific hour of a given date.
:param date_str: Date as a string in the format "YYYY-MM-DD"
:param hour: Specific hour (0 to 23)
:return: An array with shape (2,), contains mean and standard deviation for the specified hour
"""
# Convert the date string into a datetime object
date = self._convert_to_datetime(date_str)
# Calculate the day of the year (1 to 365)
day_of_year = date.timetuple().tm_yday
# Extract mean and standard deviation for the given hour
hourly_stats = self.data_year_energy[day_of_year - 1, :, hour] # Access the specific hour
hourly_stats = self.data_year_energy[
day_of_year - 1, :, hour
] # Access the specific hour
return hourly_stats
def get_stats_for_date_range(self, start_date_str, end_date_str):
@@ -58,12 +63,14 @@ class LoadForecast:
"""
start_date = self._convert_to_datetime(start_date_str)
end_date = self._convert_to_datetime(end_date_str)
start_day_of_year = start_date.timetuple().tm_yday
end_day_of_year = end_date.timetuple().tm_yday
# Note that in leap years, the day of the year may need adjustment
stats_for_range = self.data_year_energy[start_day_of_year:end_day_of_year] # -1 because indexing starts at 0
stats_for_range = self.data_year_energy[
start_day_of_year:end_day_of_year
] # -1 because indexing starts at 0
stats_for_range = stats_for_range.swapaxes(1, 0)
stats_for_range = stats_for_range.reshape(stats_for_range.shape[0], -1)
@@ -73,7 +80,9 @@ class LoadForecast:
"""Loads data from the specified file."""
try:
data = np.load(self.filepath)
self.data = np.array(list(zip(data["yearly_profiles"], data["yearly_profiles_std"])))
self.data = np.array(
list(zip(data["yearly_profiles"], data["yearly_profiles_std"]))
)
self.data_year_energy = self.data * self.year_energy
# pprint(self.data_year_energy)
except FileNotFoundError:
@@ -89,10 +98,13 @@ class LoadForecast:
"""Converts a date string to a datetime object."""
return datetime.strptime(date_str, "%Y-%m-%d")
# Example usage of the class
if __name__ == '__main__':
filepath = r'..\load_profiles.npz' # Adjust the path to the .npz file
if __name__ == "__main__":
filepath = r"..\load_profiles.npz" # Adjust the path to the .npz file
lf = LoadForecast(filepath=filepath, year_energy=2000)
specific_date_prices = lf.get_daily_stats('2024-02-16') # Adjust date as needed
specific_hour_stats = lf.get_hourly_stats('2024-02-16', 12) # Adjust date and hour as needed
specific_date_prices = lf.get_daily_stats("2024-02-16") # Adjust date as needed
specific_hour_stats = lf.get_hourly_stats(
"2024-02-16", 12
) # Adjust date and hour as needed
print(specific_hour_stats)